The impact of work pressure on decision-making effectiveness among department heads in faculties of educational sciences.

This study explores the dynamics of work pressure and decision-making effectiveness among university department heads within the context of Middle Eastern higher education. It aims to address a significant gap in the literature by answering five key questions: (1) What level of work pressure do department heads face as perceived by faculty members? (2) Does work pressure vary based on gender or years of experience? (3) How effective are department heads in decision-making? (4) Are there differences in decision-making effectiveness related to gender, university affiliation, or experience? (5) Is there a correlation between work pressure and decision-making effectiveness? A quantitative correlational research design was employed, gathering data from a questionnaire distributed to 205 faculty members. Correlational descriptive analysis revealed that department heads are subjected to high levels of work pressure but maintain a high level of decision-making effectiveness. However, significant differences in decision-making effectiveness were noted, with female faculty members performing better regardless of university affiliation or experience. A pronounced correlation was found between the intensity of work pressure and decision-making efficacy. The study underscores that department heads are under considerable work pressure, which could affect their productivity and, crucially, their decision-making processes. Universities are encouraged to take proactive steps to mitigate these pressures and promote a supportive, low-stress environment. Future research could extend this work by employing qualitative methods, including interviews and observations.

Experiences of university teachers with rotational blended learning during the COVID-19 pandemic: A qualitative case study.

This qualitative case study examines the self-efficacy of university teachers during the COVID-19 pandemic as they struggle to incorporate new technology, teaching strategies, and curriculum delivery in the shift from total remote learning to biweekly rotation learning--two weeks of face-to-face learning and two weeks online. This study was conducted over one full semester among university teachers teaching undergraduate students with the rotation model at one federal university located in the United Arab Emirates. A case study design was used as a methodology to guide this research with a primary data collection method of semi-structured interviews of 11 teachers corroborated by both in-person and online classroom observations. Participating teachers were from various colleges within the university, including medicine, education, business, law, humanities, and science. The data from the interviews and observations were analyzed using thematic analysis, which yielded the following six themes: (1) continuously changing expectations, (2) mixed feelings regarding technology self-efficacy, (3) loss of learning among undergraduate students, (4) trial and error with teaching strategies, (5) the need to consult with students in the teaching and learning process, and (6) the shift from struggle to resilience. The results of the study indicated that having clearer expectations, proper technology training, and intradepartmental collaboration may help educators overcome the challenges associated with the hybrid rotation model. These results are expounded thoroughly along with relevant implications for robust leadership practices to enhance the quality of teaching and learning during potential future crises.

A critical assessment of nanoparticles enhanced phase change materials (NePCMs) for latent heat energy storage applications.

Phase change material (PCM) laden with nanoparticles has been testified as a notable contender to increase the effectiveness of latent heat thermal energy storage (TES) units during charging and discharging modes. In this study, a numerical model is developed and implemented based on the coupling between an advanced two-phase model for the nanoparticles-enhanced PCM (NePCM) and the enthalpy-porosity formulation for the transient behavior of the phase change. Therefore, a porosity source term is added to the nanoparticles transport equation to account for the particles' frozen state in regions occupied by solid PCM. This two-phase model includes three main nanoparticles' slip mechanisms: Brownian diffusion, thermophoresis diffusion, and sedimentation. A two-dimensional model of a triplex tube heat exchanger is considered and different charging and discharging configurations are analyzed. Compared to pure PCM, results show a substantial heat transfer enhancement during the charging and discharging cycle in which a homogeneous distribution of nanoparticles is considered as the initial condition. For this case, the two-phase model predictions are superior to the ones obtained with the classical single-phase model. In the case of multi-cycle charging and discharging, a significant deterioration of the heat transfer rate is observed using the two-phase model while such assessment is senseless using the single-phase mixture model due to the physical assumptions upon which this model is formulated. The two-phase model results reveal that, for a NePCM with high nanoparticles concentration (> 1%), the melting performance during the second charging cycle is reduced by 50% compared to the first one. This performance degradation is attributed to a noteworthy non-homogeneous distribution of the nanoparticles at the beginning of the second charging cycle. The dominant nanoparticles migration mechanism, in this scenario, is the one resulting from sedimentation effects.

Relationship between lipid profile, inflammatory and endothelial dysfunction biomarkers, and type 1 diabetes mellitus: a case-control study.

OBJECTIVE: Inflammation is a major factor in endothelial dysfunction (ED) which is the earliest predictor of cardiovascular disease and premature mortality in type 1 diabetes mellitus (T1DM) patients. This study aimed to describe the possible relationship between plasma lipids and inflammatory and ED biomarkers in young Emirati patients with and without T1DM. METHODS: This case-control study included 158 patients with T1DM and 157 healthy controls from the local population of the United Arab Emirates (UAE). Anthropometric data, clinical variables, lipid profiles, liver enzymes, HbA1c, inflammatory, and ED biomarkers were measured for all participants using sophisticated techniques and assays. RESULTS: The mean ages ± SD of patients with T1DM and healthy controls was 19.3 ± 6.4 years (59.5% females) and 9.2 ± 6.8 years (61.5% females), respectively. The mean duration of T1DM was 9.3 ± 5.7 years, with HbA1c of 8.9 ± 2.1%. BMI, WC, SBP, and DBP significantly differed between the two groups. The mean lipid profiles (HDL, TG, TC, ApoA, and ApoB), liver enzymes (GGT, ALT), inflammatory (IL-6, adiponectin, TNF-α, hs-CRP), and ED biomarker levels (ICAM-1, VCAM-1, selectin, and ET-1) were also significantly different between patients and controls. Based on Spearman's rank and logistic regression analysis, there was a significant association between elevated lipid profile, liver enzymes, inflammatory markers, and ED markers in T1DM patients compared to controls. Among the biomarkers studied, ApoA, ApoB, and TC were significantly increased in T1DM patients compared to controls. CONCLUSION: This study revealed a strong association between an elevated lipid profile and inflammatory and ED markers with T1DM, which could lead to cardiovascular events in the UAE population.

Medication Adherence Among Patients with Multimorbidity in the United Arab Emirates.

Background: Multimorbidity, defined as having two or more chronic diseases, has a major impact on public health and Sustainable Development Goals (SDG). This study aims to assess the prevalence of medication adherence and associated factors among patients with multimorbidity. Methods: A questionnaire-based, cross-sectional survey was conducted by a trained interviewer across patients with multimorbidity attending outpatient clinics in two tertiary referral hospitals in the United Arab Emirates (UAE). Demographic and social variables and the outcome (self-reported adherence to long-term medication) were measured using the General Medication Adherence Scale (GMAS). Multiple logistic regression was used to assess medication adherence and associated factors. Results: From a total of 630 participants included in this study, the estimated prevalence of high medication adherence is 78.57% (±1.63478) with a 95% confidence interval (CI) [75.19, 81.61]. The odds of high medication adherence increased with age. The odds of high medication adherence for patients aged 66 years and older than those aged 19-35 years is adjusted odds ratio (AOR) = 3.880, with a 95% CI [1.124, 13.390]. Patients with income more than 50,000 had the odds, AOR = 5.169 with a 95% CI [1.282, 20.843], compared to those earning less than 10,000 Dirhams (AED). Patients aged 36-65 with health insurance coverage had higher medication adherence than groups on the other end. The number of current medications is significantly (p-value = 0.027) associated with high medication adherence with the odds of high medication adherence, AOR = 4.529 with a 95% CI [1.184, 17.326], the highest for those currently taking four medications. Conclusion: This study highlights younger population having multimorbidity in the context of an increasing life expectancy and suboptimal therapeutic outcomes. Furthermore, the study highlights multimorbidity is associated with low medication adherence and out-of-pocket payment, and non-availability of insurance is a major hindrance to medication adherence.